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Applied research in human genetics

Applied research in human genetics. Weibin Shi Michele Sale. The central focus of human genetics research:. Identification of genes that cause disease. Which polymorphisms in Which genes in Which individuals Exposed to which environmental factors Increase risk of developing disease?.

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Applied research in human genetics

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  1. Applied research in human genetics Weibin Shi Michele Sale

  2. The central focus of human genetics research: Identification of genes that cause disease Which polymorphisms in Which genes in Which individuals Exposed to which environmental factors Increase risk of developing disease?

  3. Defining what to study • As in any biomedical study, need to precisely define the disease under study • Define primary phenotype and secondary phenotypes • Understanding risk factors • Genetic or Environmental? • Ethnic differences • Age/gender influence

  4. Refining whether the disease under study is genetic • Family studies: Familial aggregation • Twin studies: Concordance rate of disorder for monozygotic twins (MZ) vs. the rate for dyzogotic (DZ) twins • Adoption studies: diseasefrequency of adoptees’ biological vs. their adopted parents or siblings • Ethnic differences

  5. Best Proof of All? Connect genetic variation to the disease!

  6. But, how do we find the gene?

  7. Linkage analysis and Association analysis are effective in identifying Mendelian disorder genes but are less effective in identifying complex disease genes

  8. Complex diseases are often caused by multiple genes and environmental factors

  9. Difficulties of genetic studies of complex disease in humans • Heterogeneity of human populations • Several to many genes involved • modest effects for any single gene • Environmental influences

  10. Mouse model of human genetic disease • Advantages over other mammals: • Small size (<40g), short generation time (8-9 wks), large litter size (5~10 puppies) • Numerous inbred strains and gene-targeted • Easy control of environmental factors

  11. Mouse genome shares great similarity with the human genome Mouse-Human Comparison 2.5 vs. 3.2 billion bp long > 99% of genes have homologs > 95% of genome “syntenic” (relative gene-order conservation)

  12. Variation among mouse strains in susceptibility to diet-induced atherosclerosis

  13. Atherosclerotic Vascular Disease

  14. Terminology • Discrete/qualitative trait - traits that are present or absent. • Continuous/quantitative trait - traits that have measurable characteristics across a range of values. This class includes the vast majority of diseases afflicting humans.

  15. Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Quantitative trait locus (QTL) analysis

  16. x B6 C3H x F1 … F2 QTL analysis starts with selection of two phenotypically different strains

  17. All F2s are analyzed for trait values

  18. All F2s are typed for genetic markers spanning the who genome

  19. Statistical analysis Map Manager QTXb20 (http://mapmgr.roswellpark.org/) and R/qtl (http://www.biostat. jhsph.edu/~kbroman/software) are available for testing the association of a phenotype with each marker. Log of the-odds-ratio (LOD) score is used to define the significance of the association of a genetic marker with a trait.

  20. Genome-wide scan for atherosclerotic lesions

  21. Interval mapping provides best estimation on the location of genes affecting atherosclerotic lesions

  22. Dissect major QTL by construction and analysis of congenic strains Congenic strain: identical to an inbred strain except for a differential chromosomal segment

  23. Sequence Comparison • If crosses include those of sequenced strains, search database for polymorphisms of positional candidate genes in the QTL regions. 15 common inbred strains (B6, AJ, 129, DBA, C3H …)now available at MGI, NCBI, and Ensembl • Re-sequence coding and promoter regions of strong candidate genes.

  24. Gene expression database • Where is your gene expressed? http://www.informatics.jax.org/javawi2/servlet/WIFetch?page=expressionQF • Is there microarry data for your gene? http://www.ncbi.nlm.nih.gov/geo/

  25. Conduct functional studies to prove the identity of promising candidate genes

  26. Test the significance of QTL genes found in mouse by association analysis using human populations

  27. Applied research in human genetics Michèle Sale, Ph.D. Center for Public Health Genomics msale@virginia.edu Tel: 982-0368

  28. National DNA Day! • April 25 • Commemorates the discovery of the structure of DNA in 1953 and the sequencing of the human genome 50 years later

  29. Genetic Information Non-Discrimination Act of 2007 (GINA) A version first introduced in 1995 GINA would: Prohibit access to individuals' personal genetic information by insurance companies making health coverage plan enrollment decisions, and by employers making hiring decisions; Prohibit insurance companies from requesting that applicants for group or individual health coverage plans be subjected to genetic testing or screening, and prohibit them from discriminating against health plan applicants based on individual genetic information; and Prohibit employers from using genetic information to refuse employment, and prohibit them from collecting employees' personal genetic information without their explicit consent. Nearly 40 states have had individual forms of the legislation in place Passed by House: April 25, 2007 (420-3), and again March 7, 2008 (as part of the Paul Wellstone Mental Health and Addiction Equity Act, 268-148) Senator Tom Coburn (R, Oklahoma) had placed hold on bill in the senate April 24, 2008: GINA passes in Senate (95-0)

  30. Some examples from GWAS for type 2 diabetes

  31. The first type 2 diabetes GWAS papers… • Sladek et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007 Feb 22; 445:881-5. • Frayling et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007 May 11; 316:889-94. • Steinthorsdottir et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007 Jun; 39:770-5. • Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007 Jun 7; 447:661-78. • Saxena et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007 Jun 1;316(5829):1331-6 • Zeggini et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007 Jun 1; 316:1336-41. • Scott et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007 Jun 1; 316:1341-5.

  32. Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research, Science 2007 Jun 1;316(5829):1331-6

  33. Association results from WTCC replication study Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007). Frayling TM. Nat Rev Genet 2007 Sep; 8:657-62

  34. Transcription-factor 7-like 2 (TCF7L2) Major new diabetes gene Identified as a diabetes gene by Grant et al.Nat Genet 2006 March; 38: 320-323 Not previously suspected to be involved in diabetes Known to influence levels of at least 60 other genes! Shown to have a role in insulin secretion (Lyssenko et al. J Clin Invest. 2007 Aug; 117:2155-63)

  35. Replicated GWAS diabetes genes

  36. Frayling TM. Nat Rev Genet 2007 Sep; 8:657-62

  37. Effect sizes of 11 confirmed diabetes variants Frayling TM. Nat Rev Genet 2007 Sep; 8:657-62

  38. TCF7L2 results

  39. But this variant is rarer inEast Asian and Native American populations • However, other variants in the same gene are associated with diabetes

  40. Investigation of “European” diabetes alleles in African Americans *Dominant model (<10 counts for minor alllele homozygote) Lewis et al. Diabetes 2008 (in press)

  41. Allele frequencies differ Lewis et al. Diabetes 2008 (in press)

  42. Can genetic information change practice in the clinic?

  43. Neonatal diabetes Mutations of the ATP-sensitive inwardly-rectifying potassium channel subunit Kir6.2 (KCNJ11) gene cause 30-58% of cases of diabetes diagnosed in patients under six months of age The majority of cases (80-90%) are de novo mutations, so won’t be identified on the basis of family history

  44. Neonatal diabetes –KCNJ11 mutations In the beta-cell, glucose metabolism increases intracellular ATP production from ADP This leads to the closure of ATP-sensitive potassium channels and membrane depolarization Subsequent activation of voltage-dependent calcium channels and influx of calcium results in insulin granule exocytosis Patients with KCNJ11 mutations have KATP channels with decreased sensitivity to ATP Channels remain open in the presence of glucose Reducing insulin secretion Pearson ER et al. N Engl J Med 2006, 355 (5), 467-477

  45. Neonatal diabetes Since patients present with hyperglycemia, undetectable C-peptide, and frequently have ketoacidosis (30%), they are often initially treated with insulin A study of 49 patients showed that 90% could successfully be treated with sulfonylureas Pearson ER et al. N Engl J Med 2006, 355 (5), 467-477

  46. Pharmacogenetics

  47. Cytochrome P450 table Stamer and Stuber. Genetic factors in pain and its treatment. Curr Opin Anaesthesiol. 2007 Oct;20(5):478-84.

  48. http://medicine.iupui.edu/flockhart/table.htm

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